Unlocking Downlink NOMA with FARIS: Joint Clustering and Surface Configuration Design

This paper investigates a fluid active reconfigurable intelligent surface (FARIS)-aided downlink non-orthogonal multiple access (NOMA) system. We formulate a network sum-rate maximization problem that jointly optimizes user clustering, NOMA power allocation, FARIS amplification gains, discrete phase shifts, and fluid element selection under quality-of-service, reflected-power, and hardware constraints. To address the resulting nonconvex mixed-integer problem, we develop a two-stage framework comprising distance-based interleaved clustering for constructing successive-interference-cancellation (SIC)-friendly user groups and per-cluster alternating optimization. The resulting subproblems are handled using geometric programming (GP), fractional programming (FP), majorization-minimization (MM) with mixed-integer phase optimization, and the cross-entropy method (CEM). Numerical results demonstrate rapid convergence, near-optimal performance relative to brute-force search (BFS)-based optimum, and consistently outperforms the benchmarks. These results verify the effectiveness of jointly integrating FARIS and NOMA for high-rate downlink transmission.

Toward Quantum-Enhanced ISAC: Active-RIS-Aided Integrated Sensing and Communication with Rydberg Atomic Receivers

In this paper, we investigate an active-RIS (ARIS)-aided integrated sensing and communication (ISAC) system with Rydberg Atomic REceiver (RARE). Leveraging the magnitude-only and real-domain observation structure of RARE, we first derive a unified ISAC model, along with a closed-form Cramer-Rao bound (CRB) for direction-of-arrival (DoA) estimation. Based on this formulation, we propose a joint design of the {base station (BS)} beamforming and ARIS reflection coefficients to minimize the CRB under RARE-specific signal-to-interference-noise-ratio (SINR) and ARIS power constraints. To tackle the resulting highly non-convex problem, we develop an alternating optimization (AO) framework that combines semidefinite relaxation (SDR) for beamforming and a majorization-minimization (MM)-based approach for ARIS design. Numerical results demonstrate that the proposed RARE-aware framework significantly outperforms conventional RF-based designs and achieves performance close to the radar-only benchmark, highlighting the potential of RARE for quantum-enhanced ISAC with ARIS.

Toward a Receiver-Induced Channel Shaping Paradigm: FRIS-Assisted Rydberg Atomic MIMO with Quadrature-Leakage-Aware Design

This paper investigates a fluid reconfigurable intelligent surface (FRIS)-assisted Rydberg Atomic REceiver (RARE) architecture under magnitude-only heterodyne readout. We show that, unlike conventional coherent systems, the optimal propagation environment is fundamentally governed by the receiver's nonlinear measurement structure. In particular, under the strong-reference regime, symbol detection is limited by residual quadrature leakage after reference alignment, motivating a receiver-induced channel shaping approach rather than conventional channel-centric optimization. Based on this insight, we formulate a signal-independent leakage minimization problem that jointly optimizes the FRIS port set, finite-resolution phase shifts, and the transmit beamformer, resulting in a nonconvex mixed discrete-continuous design. To address this, we develop an alternating-optimization (AO) framework comprising: (i) a closed-form eigenvector solution for widely-linear beamforming, (ii) cross-entropy method (CEM)-based combinatorial port selection, and (iii) coordinate-descent (CD) phase refinement with guaranteed monotonic descent. Simulation results demonstrate fast convergence and consistent bit-error-rate (BER) gains across various modulation orders and receiver dimensions. Moreover, the proposed FRIS-enabled design achieves near-exhaustive performance with significantly reduced complexity and consistently outperforms conventional RIS schemes with fixed elements, highlighting the effectiveness of spatial reconfiguration in suppressing quadrature leakage and the additional spatial degree-of-freedom (DoF) enabled by FRIS for reliable atomic-MIMO detection.

Performance Analysis and Optimization of FAS-ARIS Communications for 6G: System Modeling and Analytical Insights

This paper introduces a unified analytical and optimization framework for fluid antenna system-active reconfigurable intelligent surface (FAS-ARIS) communications in 6G. By combining the port reconfigurability of FAS with the signal amplification of ARIS, the proposed design enables more flexible control of the propagation environment and enhanced link reliability beyond what passive solutions can offer. We first derive the optimal ARIS amplification gain under a reflection power constraint to maximize the user's signal-to-noise ratio (SNR). Using a block-diagonal matrix approximation, we obtain a tractable outage expression and a tight independent-antenna equivalent upper-bound. Building on this, we establish the monotonic relationship between outage and effective channel gain, which enables a closed-form solution for ARIS phase optimization under limited channel state information (CSI). To further improve spectral efficiency, we propose a region-partitioned throughput optimization framework that achieves near-optimal performance without exhaustive search, thereby verifying its low computational complexity. Extensive simulations confirm the accuracy of the analysis and demonstrate consistent gains in outage and throughput compared to baselines.

Quantum-PROBE: Rydberg Atomic Receiver-Based Multi-AoA Estimation with RF Lens

This paper presents the Quantum-Power pROfile Based Estimation (PROBE) framework, a Rydberg Atomic Receiver (RARE)-based multi-user angle-of-arrival (AoA) estimation approach equipped with a radio-frequency (RF) lens front end. We establish a physics-consistent analytical model showing that magnitude-only RARE measurements, processed via the beam-propagation method (BPM) and snapshot-wise power accumulation, can be rigorously characterized as a nonnegative superposition of AoA-dependent, lens-induced spatial power profiles. This formulation reveals a structured and interpretable power-domain dictionary that enables multi-user AoA recovery without explicit phase reconstruction. Building on this foundation, we develop two complementary recovery strategies: (i) a principled non-negative least absolute shrinkage and selection operator (NN-LASSO)-based solver that estimates a sparse nonnegative angular representation via an accelerated proximal-gradient method followed by cluster-based AoA decoding, and (ii) a low-complexity successive interference cancellation (SIC) algorithm that iteratively identifies and removes dominant power-profile components through cosine-similarity matching. Simulation results demonstrate that the proposed Quantum-PROBE framework consistently outperforms representative RARE- and RF-based benchmarks across diverse system configurations, while offering a clear accuracy-complexity tradeoff between the NN-LASSO and SIC variants for practical quantum sensing deployments.

Beamforming Gain Maximization for Fluid Reconfigurable Intelligent Surface: A Minkowski Geometry Approach

This paper investigates beamforming-gain maximization for a fluid reconfigurable intelligent surface (FRIS)-assisted downlink system, where each active port applies a finite-resolution unit-modulus phase selected from a discrete codebook. The resulting design couples the multi-antenna base-station (BS) beamformer with combinatorial FRIS port selection and discrete phase assignment, leading to a highly nonconvex mixed discrete optimization. To address this challenge, we develop an alternating-optimization (AO) framework that alternates between a closed-form maximum-ratio-transmission (MRT) update at the BS and an {optimal} FRIS-configuration update. The key step of the proposed FRIS configuration is a Minkowski-geometry reformulation of the FRIS codebook superposition: by convexifying the feasible reflected-sum set and exploiting support-function identities, we convert the FRIS subproblem into a one-dimensional maximization over a directional parameter. For each direction, the optimal configuration is obtained constructively via per-port directional scoring, Top-$M_o$ port selection, and optimal codeword assignment. For the practically important regular $M_p$-gon phase-shifter codebook, we further derive closed-form score expressions and establish a piecewise-smooth structure of the resulting support function, which leads to a finite critical-angle search that provably identifies the global optimum without exhaustive angular sweeping. Simulation results demonstrate that the proposed framework consistently outperforms benchmarks, achieves near-optimal beamforming gains in exhaustive-search validations, accurately identifies the optimal direction via support-function maximization, and converges rapidly within a few AO iterations.

Ampli-Flection for 6G: Active-RIS-Aided Aerial Backhaul with Full 3D Coverage

In this paper, we propose a novel aerial backhaul architecture that employs an aerial active reconfigurable intelligent surface (RIS) to achieve energy-efficient, {full 3D coverage including UAV-BSs and ground users in 6G wireless networks}. Unlike prior aerial-RIS approaches limited to {2D coverage with only servicing ground users} or passive operation, the proposed design integrates an active-RIS onto a high-altitude aerial platform, enabling reliable line-of-sight links and overcoming multiplicative fading through amplification. In a scenario with UAV-BSs deployed to handle sudden traffic surges in urban areas, the aerial-active-RIS both reflects and amplifies backhaul signals to overcome blockage. We jointly optimize the aerial platform placement, array partitioning, and RIS phase configuration to maximize UAV-BS energy-efficiency. Simulation results confirm that the proposed method significantly outperforms benchmarks, demonstrating its strong potential to deliver resilient backhaul connectivity with comprehensive 3D coverage in 6G networks.

RIS-aided ISAC with $K$-Rydberg Atomic Receivers

In this paper, we investigate a reconfigurable intelligent surface (RIS)-assisted integrated sensing and communications (ISAC) framework equipped with multiple Rydberg atomic receiver (RAR)-aided users. By leveraging the reference-assisted reception mechanism of RARs, we develop a unified signal model that jointly captures downlink multi-user communication with RARs and monostatic radar sensing. To explicitly balance communication performance and sensing accuracy, we formulate a Cramer-Rao bound (CRB)-constrained utility maximization problem. To address these challenges, we propose a joint optimization framework that combines fractional programming (FP), majorization-minimization (MM), and the alternating direction method of multipliers (ADMM). Simulation results demonstrate that the proposed framework consistently outperforms the conventional approach over a wide range of system environments, thereby highlighting the importance of the proposed framework in unlocking the potential of RARs for 6G.

FARIS: Fluid-Active-RIS

In this paper, we introduce a fluid-active reconfigurable intelligent surface (FARIS) that combines fluid-based port repositioning with per-element active amplification to enhance the performance of 6G network. To characterize the performance, we formulate an ergodic-rate maximization problem that jointly optimizes both the active amplification-reflection vector and the discrete selection of fluid active elements under practical hardware constraints. The problem is addressed via an alternating optimization (AO) framework, which progressively improves the rate. Complexity and convergence analyses that follow furnish deeper insight into the algorithmic operation and performance enhancement. Numerical results confirm that the proposed FARIS with AO framework consistently outperforms conventional FRIS/ARIS, delivering higher rates across diverse environments, often even when using fewer active elements or a smaller physical aperture.

Measurement-based Close-in Path Loss Modeling with Diffraction for Rural Long-distance Communications

In this letter, we investigate rural large-scale path loss models based on the measurements in a central area of South Korea (rural area) in spring. In particular, we develop new close-in (CI) path loss models incorporating a diffraction component. The transmitter used in the measurement system is located on a hill and utilizes omnidirectional antennas operating at 1400 and 2250 MHz frequencies. The receiver is also equipped with omnidirectional antennas and measures at positions totaling 3,858 (1,262 positions for LOS and 2,596 positions for NLOS) and 4,957 (1,427 positions for LOS and 3,530 positions for NLOS) for 1400 and 2250 MHz, respectively. This research demonstrates that the newly developed CI path loss models incorporating a diffraction component significantly reduce standard deviations (STD) and are independent of frequency, especially for LOS beyond the first meter of propagation, making them suitable for use with frequencies up to a millimeter-wave.